About
About
Concept
Hereditary Neuromuscular Diseases (HNMDs) are genetic and inherited diseases that cause progressive muscle weakness and atrophy, affect the degree of mobility and can lead to long-term general disability.
The disability induced by HNMD prevents patients’ full participation in public life with an additional social burden since HNMD often occurs in young people and loss of independence implies lack of social participation, assistance from family members or caregivers, and can lead to long-term institutionalisation and hospitalisation.
Concept
Hereditary Neuromuscular Diseases (HNMDs) are genetic and inherited diseases that cause progressive muscle weakness and atrophy, affect the degree of mobility and can lead to long-term general disability.
The disability induced by HNMD prevents patients’ full participation in public life with an additional social burden since HNMD often occurs in young people and loss of independence implies lack of social participation, assistance from family members or caregivers, and can lead to long-term institutionalisation and hospitalisation.
Through time, DNA molecular analysis has become the gold standard for diagnostics, adopting the link “one gene one phenotype” and assuming a “genotype first” approach.
The limit of this approach is that HNMD patients present similar characteristics, similar changes in muscle imaging and/or muscle histology, and yet some may carry mutations in different genes and others may have no obvious harmful variants.
HNMDs may result from complex biological interactions, mostly still unknown, and the HNMD diagnosis is currently extremely difficult.
The lack of understanding hinders the definition of a proper prognosis, with a devastating impact on patients’ life, and prevents the development of efficacious treatments for most of these diseases.
Through time, DNA molecular analysis has become the gold standard for diagnostics, adopting the link “one gene one phenotype” and assuming a “genotype first” approach.
The limit of this approach is that HNMD patients present similar characteristics, similar changes in muscle imaging and/or muscle histology, and yet some may carry mutations in different genes and others may have no obvious harmful variants.
HNMDs may result from complex biological interactions, mostly still unknown, and the HNMD diagnosis is currently extremely difficult.
The lack of understanding hinders the definition of a proper prognosis, with a devastating impact on patients’ life, and prevents the development of efficacious treatments for most of these diseases.
Approach
CoMPaSS-NMD exploits information already acquired from previous studies funded by the European Union to create, through AI-based computational methods, systems for grouping patients on the basis of integrated data from genetic analysis and Nuclear Magnetic Resonance (NMR) imaging and will validate these methods on a cohort of patients who will be evaluated in depth by acquiring data from clinical, genomic, morphological, histological and NMR imaging evaluations with standardised methods.
The study consists of two parts:
1) a retrospective observational study conducted on genetic, histopathology and MRI data which will use existing data collected from centres in Great Britain (UNEW), France (CERBM) , Finland (SFF), and Italy (FSM). These data are used to design algorithms of Machine Learning (ML), a branch of AI and Computet Science, able to identify relationships between data that are not recognizable with standard analytical methods.
2) a prospective study involving the collection of clinical, genomic, histopathological, and MRI data obtained from 500 patients suffering from hereditary neuromuscular diseases (HNMD) who have not received a diagnosis. These data from clinical centres, partners of the CoMPaSS-NMD consortium in Italy (FSM, UNIMORE) and Germany (LMUM ), are used to validate the ML algorithms designed in the previous phase of the study.
The previous and new data are analysed using unsupervised clustering algorithms, used to process raw, unclassified data into groups of patients to identify common clinical patterns to constitute the CoMPaSS-NMD Atlas.
The CoMPaSS-NMD impact
CoMPaSS-NMD will lead to a paradigm-shift in the diagnosis, prognosis and treatment of HNMD patients. The new approach integrates four patient’s data: clinical, genetical, from RM images and histopathological data, by using AI-based tools as a support to specialists.
This approach will lead to a faster and more accurate diagnosis of HNMD, incrementing the diagnostic rate by 30% and promoting effective actions by European national health systems, ameliorating the quality of life of patients and caregivers, reducing time to diagnose and start the treatment, and, in turn, needless expenses.
Ethics and compliance with the EU legislation
Ethics and compliance with current and future legislation, especially regarding data privacy, data minimization, and data access rights, are crucial for a research project like CoMPaSS-NMD that analyse personal health-related data of patients.
Therefore, a whole work package is dedicated to considering ethical, regulatory and legislative aspects of the research in this EU project and its implementation in the CoMPaSS-NMD Neuromuscular Genome Atlas (NMDGA).
The consortium of the CoMPaSS-NMD project is aware of the importance of privacy protection of patients and other stakeholders. With this aim, the consortium signed a Joint Controller Agreement where the partners state that are joint controllers of the data processed within the project according to the Article 26 of the European “General Data Protection Regulation” (Regulation (EU) 2016/679, GDPR) and all other applicable national or European Union legislation on the matter. Data Protection Impact Assessments to evaluate and mitigate the risks related to the mentioned personal data process have been performed as well.
Moreover, the project consortium is exploring new approaches of protecting personal data by design such as Federated learning. This means that we apply training of machine learning algorithms for stratification and classification on multiple local datasets contained in the six local clinical project partners without explicitly exchanging data samples of patients.
Approach
CoMPaSS-NMD exploits information already acquired from previous studies funded by the European Union to create, through AI-based computational methods, systems for grouping patients on the basis of integrated data from genetic analysis and Nuclear Magnetic Resonance (NMR) imaging and will validate these methods on a cohort of patients who will be evaluated in depth by acquiring data from clinical, genomic, morphological, histological and NMR imaging evaluations with standardised methods.
The study consists of two parts:
1) a retrospective observational study conducted on genetic, histopathology and MRI data which will use existing data collected from centres in Great Britain (UNEW), France (CERBM) , Finland (SFF), and Italy (FSM). These data are used to design algorithms of Machine Learning (ML), a branch of AI and Computet Science, able to identify relationships between data that are not recognizable with standard analytical methods.
2) a prospective study involving the collection of clinical, genomic, histopathological, and MRI data obtained from 500 patients suffering from hereditary neuromuscular diseases (HNMD) who have not received a diagnosis. These data from clinical centres, partners of the CoMPaSS-NMD consortium in Italy (FSM, UNIMORE) and Germany (LMUM ), are used to validate the ML algorithms designed in the previous phase of the study.
The previous and new data are analysed using unsupervised clustering algorithms, used to process raw, unclassified data into groups of patients to identify common clinical patterns to constitute the CoMPaSS-NMD Atlas.
The CoMPaSS-NMD impact
CoMPaSS-NMD will lead to a paradigm-shift in the diagnosis, prognosis and treatment of HNMD patients. The new approach integrates four patient’s data: clinical, genetical, from RM images and histopathological data, by using AI-based tools as a support to specialists.
This approach will lead to a faster and more accurate diagnosis of HNMD, incrementing the diagnostic rate by 30% and promoting effective actions by European national health systems, ameliorating the quality of life of patients and caregivers, reducing time to diagnose and start the treatment, and, in turn, needless expenses.
Ethics and compliance with the EU legislation
Ethics and compliance with current and future legislation, especially regarding data privacy, data minimization, and data access rights, are crucial for a research project like CoMPaSS-NMD that analyse personal health-related data of patients.
Therefore, a whole work package is dedicated to considering ethical, regulatory and legislative aspects of the research in this EU project and its implementation in the CoMPaSS-NMD Neuromuscular Genome Atlas (NMDGA).
The consortium of the CoMPaSS-NMD project is aware of the importance of privacy protection of patients and other stakeholders. With this aim, the consortium signed a Joint Controller Agreement where the partners state that are joint controllers of the data processed within the project according to the Article 26 of the European “General Data Protection Regulation” (Regulation (EU) 2016/679, GDPR) and all other applicable national or European Union legislation on the matter. Data Protection Impact Assessments to evaluate and mitigate the risks related to the mentioned personal data process have been performed as well.
Moreover, the project consortium is exploring new approaches of protecting personal data by design such as Federated learning. This means that we apply training of machine learning algorithms for stratification and classification on multiple local datasets contained in the six local clinical project partners without explicitly exchanging data samples of patients.
CONSORTIUM
CONSORTIUM
UNIMORE has a strong vocational aspect having important collaboration with leading groups in the development of research, teaching programmes, innovation diagnostics and therapies. The aim is to study the morphology, biochemistry, physiology and pathology of biological processes, including the search for new pharmacological approaches and therapies related to HNMDs.
UNIMORE will coordinate the whole project life cycle and will be responsible for monitoring the activities. UNIMORE will ensure the project implementation progress and the clinical and genomic study of cases with NMDs to test and clinically validate computational models to guide patient stratification.
The Silesian University of Technology (SUT) is the oldest technical university in Upper Silesia and one of the largest in the country. It was established in 1945 as a scientific and educational facility for the most industrialised area in Poland, and one of the most industrialised in Europe.
For over 75 years it has been an important institution of public life. It plays a significant cultural and opinion-forming role in the region.
SUT leads the standardisation and the analysis of the MRI and muscle histological scan, and develops both AI-guided clustering and classification systems.
The Foundation carries out research in the field of neuroscience with activities related to 5 main areas, including: 1) Developmental Neurology; 2) Neurogenetics and Epileptology; 3) Psychopharmacology; 4) Psychiatric Genetics, and Psychotherapy; 5) Neuroimaging.
FSM – IRCCS Fondazione Stella Maris will provide patients and data, especially contributing in the definition and the standardisation of clinical and histopathological data.
The goal of the leading private research and technology organisation in Spain is to transform research into prosperity to improve people’s quality of life. The areas Personalised Health and Digital Transformation apply Artificial Intelligence to prevention, diagnostics, therapy and rehabilitation.
TEC leads the work on ethics and is in charge of federated learning for clustering and classification.
The hospital of the Ludwig-Maximilians-University (LMU) Munich, Germany is a center of high-end medicine, medical innovation and research. The hospital enables an individual and safe patient care. Employees of the Medical Center represent 90 countries. Hospital and Medical Faculty programs support patient care and research projects in several countries around the world. With more than 2.000 beds the University Hospital of Munich (LMU) is a highly advanced hospital with 47 clinics, institutes and departments covering all fields of medicine. With its two campuses in Munich, Grosshadern and in the city center, it is one of the largest hospitals in Europe.
LMUM leads the work on the data format standardisation procedures and requirements for clinical and morphological data.
The CERBM hosts the IGBMC institute which missions are to 1) develop knowledge on living organisms, 2) translate the findings to industrial applications, and 3) train the future scientists.
The CERBM-IGBMC will take part to several workpackages and tasks of the COMPASS project, with special emphasis on the genetic characterization of patients with neuromuscular diseases.
The Folkhälsan Research Center, responsible for Folkhälsan’s research activities, is an internationally renowned unit with focus on biomedical and health research within programs on genetics and public health.
In CoMPaSS-NMD, Folkhalsan Research Center at Samfundet Folkhalsan y Svenska Finland (SFF) will coordinate task 2.2 and will contribute to other work packages and tasks. DNA and RNA sequencing and data analysis as well as muscle pathology, data analysis, muscle pathology, and imaging.
SFF provides access to large sets of clinical, histopathological, imaging, and genetic data that provide the bases for the CoMPaSS-NMD Atlas.
Deep Blue addresses ultimate socio-technical challenges through research and consultancy, helping organisations innovate and grow their businesses through human-centred design solutions.
In CoMPaSS-NMD, Deep Blue facilitates the introduction of the new AI-based system in the daily routine of doctors with particular attention to the related critical aspects: security, transparency and responsibility in the use of data of patients. DBL is leading the project communication from the development phase up to the market launch and use of the system by end-users.
CeGaT is a global provider of genetic analyses for a wide range of medical, research, and pharmaceutical applications. Founded 2009 in Tübingen, Germany, the company combines state-ofthe-art sequencing technology with medical expertise – with the aim of identifying the genetic causes of diseases and supporting patient care. For researchers and pharmaceutical companies, CeGaT offers a broad portfolio of sequencing services and tumor analyses. CeGaT generates the data basis for clinical studies and medical innovations and drives science forward with its own insights.
In CoMPaSS-NMD, CeGaT will ensure the highest quality of the results obtained through sequencing.
Fincons Group is an IT Business Consultancy and System Integrator with 40 years of experience and offices in Europe and the US. The Group provides services and solutions in strategy, consulting, digital, technology and operations to different industries. Its International Institutions and Research Business Unit leverages innovation drivers developing collaborations with industrial and public partners, research centres and universities. Its Lab is actively involved in R&D activities in several areas among which: Augmented Reality, Artificial Intelligence, Blockchain, IoT, Privacy and Security.
Fincons Group has the role of system integrator and leads WP4, in which the CoMPaSS ATLAS platform is generated.
The John Walton Muscular Dystrophy Research Centre at the Centre for Life, supports both The Newcastle Upon Tyne Hospital Trust and Newcastle University. Launched in November 2014, the Centre brings together and consolidates Newcastle’s distinguished, international and world-leading record in research and care for neuromuscular diseases.
The JWMDRC (UNEW) leads the work on the definition and standardisation of genetic and MRI Imaging data and contributes to the task on centre-specific MRI-based patient clustering and profiling.
UNIMORE has a strong vocational aspect having important collaboration with leading groups in the development of research, teaching programmes, innovation diagnostics and therapies. The aim is to study the morphology, biochemistry, physiology and pathology of biological processes, including the search for new pharmacological approaches and therapies related to HNMDs.
UNIMORE will coordinate the whole project life cycle and will be responsible for monitoring the activities. UNIMORE will ensure the project implementation progress and the clinical and genomic study of cases with NMDs to test and clinically validate computational models to guide patient stratification.
The Silesian University of Technology (SUT) is the oldest technical university in Upper Silesia and one of the largest in the country. It was established in 1945 as a scientific and educational facility for the most industrialised area in Poland, and one of the most industrialised in Europe.
For over 75 years it has been an important institution of public life. It plays a significant cultural and opinion-forming role in the region.
SUT leads the standardisation and the analysis of the MRI and muscle histological scan, and develops both AI-guided clustering and classification systems.
The Foundation carries out research in the field of neuroscience with activities related to 5 main areas, including: 1) Developmental Neurology; 2) Neurogenetics and Epileptology; 3) Psychopharmacology; 4) Psychiatric Genetics, and Psychotherapy; 5) Neuroimaging.
FSM – IRCCS Fondazione Stella Maris will provide patients and data, especially contributing in the definition and the standardisation of clinical and histopathological data.
The goal of the leading private research and technology organisation in Spain is to transform research into prosperity to improve people’s quality of life. The areas Personalised Health and Digital Transformation apply Artificial Intelligence to prevention, diagnostics, therapy and rehabilitation.
TEC leads the work on ethics and is in charge of federated learning for clustering and classification.
The hospital of the Ludwig-Maximilians-University (LMU) Munich, Germany is a center of high-end medicine, medical innovation and research. The hospital enables an individual and safe patient care. Employees of the Medical Center represent 90 countries. Hospital and Medical Faculty programs support patient care and research projects in several countries around the world. With more than 2.000 beds the University Hospital of Munich (LMU) is a highly advanced hospital with 47 clinics, institutes and departments covering all fields of medicine. With its two campuses in Munich, Grosshadern and in the city center, it is one of the largest hospitals in Europe.
LMUM leads the work on the data format standardisation procedures and requirements for clinical and morphological data.
The CERBM hosts the IGBMC institute which missions are to 1) develop knowledge on living organisms, 2) translate the findings to industrial applications, and 3) train the future scientists.
The CERBM-IGBMC will take part to several workpackages and tasks of the COMPASS project, with special emphasis on the genetic characterization of patients with neuromuscular diseases.
The Folkhälsan Research Center, responsible for Folkhälsan’s research activities, is an internationally renowned unit with focus on biomedical and health research within programs on genetics and public health.
In CoMPaSS-NMD, Folkhalsan Research Center at Samfundet Folkhalsan y Svenska Finland (SFF) will coordinate task 2.2 and will contribute to other work packages and tasks. DNA and RNA sequencing and data analysis as well as muscle pathology, data analysis, muscle pathology, and imaging.
SFF provides access to large sets of clinical, histopathological, imaging, and genetic data that provide the bases for the CoMPaSS-NMD Atlas.
Deep Blue addresses ultimate socio-technical challenges through research and consultancy, helping organisations innovate and grow their businesses through human-centred design solutions.
In CoMPaSS-NMD, Deep Blue facilitates the introduction of the new AI-based system in the daily routine of doctors with particular attention to the related critical aspects: security, transparency and responsibility in the use of data of patients. DBL is leading the project communication from the development phase up to the market launch and use of the system by end-users.
CeGaT is a global provider of genetic analyses for a wide range of medical, research, and pharmaceutical applications. Founded 2009 in Tübingen, Germany, the company combines state-ofthe-art sequencing technology with medical expertise – with the aim of identifying the genetic causes of diseases and supporting patient care. For researchers and pharmaceutical companies, CeGaT offers a broad portfolio of sequencing services and tumor analyses. CeGaT generates the data basis for clinical studies and medical innovations and drives science forward with its own insights.
In CoMPaSS-NMD, CeGaT will ensure the highest quality of the results obtained through sequencing.
Fincons Group is an IT Business Consultancy and System Integrator with 40 years of experience and offices in Europe and the US. The Group provides services and solutions in strategy, consulting, digital, technology and operations to different industries. Its International Institutions and Research Business Unit leverages innovation drivers developing collaborations with industrial and public partners, research centres and universities. Its Lab is actively involved in R&D activities in several areas among which: Augmented Reality, Artificial Intelligence, Blockchain, IoT, Privacy and Security.
Fincons Group has the role of system integrator and leads WP4, in which the CoMPaSS ATLAS platform is generated.
The John Walton Muscular Dystrophy Research Centre at the Centre for Life, supports both The Newcastle Upon Tyne Hospital Trust and Newcastle University. Launched in November 2014, the Centre brings together and consolidates Newcastle’s distinguished, international and world-leading record in research and care for neuromuscular diseases.
The JWMDRC (UNEW) leads the work on the definition and standardisation of genetic and MRI Imaging data and contributes to the task on centre-specific MRI-based patient clustering and profiling.
Scientific Advisory Board
Scientific Advisory Board